Rationality in context: An analogical perspective

Autor(en): Besold, T.R.
Stichwörter: Algorithmic approach; Analysis and modeling; Background theory; Cognitive mechanisms; Computational model; Ecological rationality; Human decision-making; Rational behavior, Decision making, Behavioral research
Erscheinungsdatum: 2013
Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen: 8175 LNAI
Startseite: 129
Seitenende: 142
Zusammenfassung: 
At times, human behavior seems erratic and irrational. Therefore, when modeling human decision-making, it seems reasonable to take the remarkable abilities of humans into account with respect to rational behavior, but also their apparent deviations from the normative standards of rationality shining up in certain rationality tasks. Based on well-known challenges for human rationality, together with results from psychological studies on decision-making and from previous work in the field of computational modeling of analogy-making, I argue that the analysis and modeling of rational belief and behavior should also consider context-related cognitive mechanisms like analogy-making and coherence maximization of the background theory. Subsequently, I conceptually outline a high-level algorithmic approach for a Heuristic Driven Theory Projection-based system for simulating context-dependent human-style rational behavior. Finally, I show and elaborate on the close connections, but also on the significant differences, of this approach to notions of "ecological rationality". © 2013 Springer-Verlag.
Beschreibung: 
Conference of 8th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2013 ; Conference Date: 28 October 2013 Through 31 October 2013; Conference Code:101219
ISBN: 9783642409714
ISSN: 03029743
DOI: 10.1007/978-3-642-40972-1_10
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84889584975&doi=10.1007%2f978-3-642-40972-1_10&partnerID=40&md5=58363d2395e202aa1a3e3317f17b952c

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